code: def test_revgnn_with_args(num_groups):
      x = torch.randn(4, 32)
      edge_index = torch.tensor([[0, 1, 2, 3], [0, 0, 1, 1]])
      edge_weight = torch.rand(4)
  
      lin = Linear(32, 32)
      conv = GraphConv(32 // num_groups, 32 // num_groups)
      conv = GroupAddRev(conv, num_groups=num_groups)
  
      h = lin(x)
      out = conv(h, edge_index, edge_weight)
      target = out.mean()
      target.backward()
  
file_path: pytorch_geometric/test/nn/models/test_rev_gnn.py
imports: import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.nn import GraphConv, GroupAddRev, SAGEConv
  from torch_geometric.nn.dense.linear import Linear
label_desc: Use image node_id 5 for calling a global function with example usage: test_revgnn_with_args(num_groups) without return types